As the use of images for event detection or recognition becomes more pervasive, efficient ways of analyzing images becomes essential. Generally, analyzing images for event detection or recognition consists of capturing the images and analyzing the captured images using human operators. For example, images of an entrance into a building or room captured by a video camera are maintained such that a human operator subsequently reviews the captured images to determine whether a person has entered the building or room. In this situation, the human operator must constantly monitor the captured images to determine an occurrence of an event or an existence of a condition, and a significant amount of captured images that need to be monitored must be transmitted from the video camera.
A typical system for capturing and analyzing images requires that image signals be carried over dedicated coaxial cable, fiber optic line, etc., and further requires that electrical power be supplied to support continuous operation. Thus, the cost of the typical system is significant.
Other solutions for image processing have been proposed where processing of captured images is implemented using a processor in an image capturing device such that an alert or an alarm is triggered when a change occurs. For example, an image capturing device, such a camera in front of a store, may be provided with a processor for processing images captured by the camera so that the camera triggers an alarm when a number of pixels between consecutive images exceeds a certain threshold. However, a processor installed on a camera has limited capability due to size, weight, cost, power limitations, etc., and thus, does not enable complex event detection or recognition. Further, due to the limited processing capability of the processor installed on the camera, accurate event detection or recognition can not be implemented, thereby increasing the rate of false alerts or alarms.
Accordingly, it is important to provide intelligent distributed analyses of images for efficient event detection or recognition. This becomes especially important as image analysis continues to be necessitated by different purposes, such as for security purposes, etc. Thus, there is a need for intelligent distributed analyses of images that addresses the above-mentioned and other limitations.